CD44 Anti-Human, FITC

What is CD44 and why is it an important target for immunological research?

CD44 is an 80-95 kDa glycosylated type I transmembrane protein that functions as a cell-surface receptor mediating cell-cell and cell-matrix interactions primarily through its affinity for hyaluronic acid (HA) and possibly other ligands. It plays crucial roles in cellular processes including:

• Cell migration and tumor growth progression

• Lymphocyte activation and recirculation

• Homing to peripheral lymphoid organs and inflammation sites

• Leukocyte attachment to and rolling on endothelial cells

CD44 is widely expressed on leukocytes, erythrocytes, epithelial cells, and mesenchymal cells, but is notably negative on platelets and hepatocytes . Its expression increases as B and T cells become activated or progress to memory stage, making it a valuable marker for memory cell subsets . Additionally, CD44 has been recognized as a molecular marker for cancer stem cells, further expanding its research significance .

What are the differences between commercially available CD44 Anti-Human, FITC antibody clones?

Different CD44 Anti-Human, FITC antibody clones vary in their species reactivity, epitope recognition, and performance characteristics. Here's a comparative analysis of common clones:

When selecting a clone, researchers should consider:

• The species being studied (some clones like IM7 offer broader cross-reactivity)

• The specific CD44 epitope of interest

• Published validation data for your specific application

• The compatibility with other antibodies in multicolor panels

What is the typical preparation and storage protocol for CD44 Anti-Human, FITC antibodies?

Proper handling of CD44 Anti-Human, FITC antibodies is essential for maintaining performance:

Preparation:

• Most antibodies are pre-diluted for use at recommended volumes (typically 5 μl per 10^6 cells in 100 μl suspension or 5 μl per 100 μl of whole blood)

• An isotype control should be used at the same concentration as the CD44 antibody

• For flow cytometry, the standard protocol involves incubating cells with the antibody for 20-30 minutes at 2-8°C protected from light

Storage Conditions:

• Store at 2-8°C (refrigerated, do not freeze)

• Protect from prolonged exposure to light to prevent photobleaching of FITC

• Most formulations can be stored for 12 months from the date of receipt when properly maintained

• Antibodies are typically provided in phosphate-buffered solution (pH 7.2) containing stabilizers such as sodium azide (0.09%) and protein protectants (BSA or gelatin)

Handling Precautions:

• Sodium azide yields toxic hydrazoic acid under acidic conditions; dilute azide compounds in running water before discarding

• Allow refrigerated antibodies to equilibrate to room temperature before opening

• Return to refrigerated storage promptly after use

What are the optimal staining protocols for CD44 Anti-Human, FITC in different sample types?

Staining protocols should be optimized based on sample type:

For Peripheral Blood:

• For whole blood: Use 100 μl of blood, add 5 μl of CD44 Anti-Human, FITC antibody

• Incubate for 20-30 minutes at 2-8°C in the dark

• Lyse red blood cells using commercial lysing buffer (e.g., BD Pharm Lyse™)

• Wash cells 2-3 times with PBS containing 0.5% BSA

• Resuspend in appropriate buffer for flow cytometric analysis

For Isolated PBMCs:

• Adjust cell concentration to 1 × 10^6 cells in 100 μl of staining buffer

• Add 5 μl of CD44 Anti-Human, FITC antibody

• Incubate for 20-30 minutes at 2-8°C in the dark

• Wash twice with staining buffer

• Resuspend in 300-500 μl of buffer for analysis

For Cell Lines:

• Harvest cells using a method that preserves surface epitopes (preferably non-enzymatic)

• If using trypsin, allow a recovery period of 1-2 hours in complete media

• Wash cells and adjust to 1 × 10^6 cells per 100 μl

• Stain with titrated amount of antibody (typically 5 μl)

• Include appropriate controls (unstained and isotype)

The flow cytometric analysis should be performed using instruments with appropriate laser/filter configuration: blue laser (488 nm) excitation and detection using an optical filter centered near 530 nm (e.g., 525/40 nm bandpass filter) .

What controls are essential when using CD44 Anti-Human, FITC in flow cytometry experiments?

A comprehensive control strategy is crucial for reliable CD44 antibody experiments:

Essential Controls:

• Isotype Control: A FITC-conjugated antibody of the same isotype, host species, and concentration as the CD44 antibody (e.g., FITC Mouse IgG2b, κ for G44-26 clone) to assess non-specific binding.

• Unstained Control: Cells processed identically but without antibody addition to determine autofluorescence levels.

• Single-Color Controls: If performing multicolor cytometry, include single-stained samples for each fluorochrome to calculate compensation.

• Positive Control: A known CD44-expressing cell population such as human peripheral blood lymphocytes, which show reliable CD44 expression patterns .

• Negative Control: If available, include a known CD44-negative population such as platelets to confirm specificity.

Specialized Controls for Advanced Applications:

• Fluorescence Minus One (FMO): Samples stained with all fluorochromes except FITC to establish proper gating boundaries.

• Blocking Controls: Pre-incubate cells with unlabeled CD44 antibody before adding FITC-conjugated antibody to confirm binding specificity.

• Dead Cell Discrimination: Include viability dye since dead cells can bind antibodies non-specifically.

Proper implementation of these controls enables confident interpretation of CD44 expression patterns and facilitates troubleshooting when unexpected results occur.

How can I optimize CD44 Anti-Human, FITC antibody performance in multiparameter flow cytometry?

Optimizing CD44 antibody performance in complex panels requires systematic approach:

Antibody Titration:

• Prepare serial dilutions of the antibody (e.g., 1:2, 1:4, 1:8, etc.)

• Stain identical cell samples with each dilution

• Calculate staining index: (MFI positive - MFI negative) / (2 × SD of negative)

• Select concentration with highest staining index, not necessarily strongest signal

Panel Design Considerations:

• Account for spectral overlap between FITC and other fluorochromes (particularly PE)

• Consider CD44 expression level when selecting fluorochrome (FITC is moderate brightness)

• Balance bright fluorochromes with dimly expressed antigens and vice versa

• Use online panel design tools that account for instrument configuration

Buffer Optimization:

• Include protein (0.5-1% BSA) to reduce non-specific binding

• For samples with high Fc receptor expression, include Fc blocking reagent

• Maintain consistent pH (7.2-7.4) for optimal FITC performance

Sample Processing Refinements:

• Standardize time from collection to staining

• Optimize red cell lysis conditions if using whole blood

• Consider gentle cell dissociation methods for adherent cells or tissues

• Implement temperature control during staining (typically 2-8°C)

Instrument Settings:

• Establish target values for positive populations using application-specific settings

• Use standardization beads to maintain consistent PMT voltages

• Implement quality control procedures to track instrument performance

These optimization steps ensure maximum sensitivity and specificity when detecting CD44 in complex cellular samples.

How can CD44 Anti-Human, FITC be utilized to identify and isolate cancer stem cells?

CD44 has emerged as an important marker for cancer stem cells (CSCs) across multiple tumor types, though protocols must be carefully optimized:

Identification Strategy:

• CD44 is typically used in combination with other markers to identify CSC populations

• Common co-markers include CD24 (breast cancer), CD133 (colorectal cancer), and EpCAM

• Analyze CD44 as high/intermediate/low expression rather than simply positive/negative

• Implement multi-parameter gating strategies that incorporate functional CSC markers (e.g., ALDH activity)

Isolation Protocol:

• Prepare single-cell suspensions from tumor samples using gentle enzymatic digestion

• Block Fc receptors to prevent non-specific binding

• Stain with titrated CD44 Anti-Human, FITC antibody and additional CSC markers

• Include viability dye to exclude dead cells

• Sort CD44high cells using FACS with appropriate gating strategy

• Verify stemness of isolated populations using functional assays

Functional Validation Assays:

• Sphere formation in non-adherent, serum-free conditions

• In vitro clonogenic assays demonstrating self-renewal

• In vivo limiting dilution transplantation assays

• Chemotherapy/radiation resistance testing

• Differentiation capacity analysis

Technical Considerations:

• Fresh samples typically yield more reliable results than frozen specimens

• CD44 expression may be affected by prolonged ex vivo culture

• Enzymes used for tissue dissociation may affect CD44 epitopes

• CSC frequency varies dramatically across tumor types and subtypes

The specific CD44 antibody clone should be selected based on validation data in your tumor type of interest, as epitope accessibility may vary between different malignancies .

What methods can be used to quantify absolute CD44 expression levels in research samples?

Standardized quantification of CD44 expression enables more meaningful comparisons:

Absolute Quantification Methods:

• Antibody Binding Capacity (ABC) Determination:

  • Use calibrated beads with known antibody binding capacity

  • Establish standard curve relating fluorescence to number of antibodies bound

  • Convert sample fluorescence to molecules per cell

  • Account for antibody:fluorochrome ratio (F:P ratio)

• Molecules of Equivalent Soluble Fluorochrome (MESF):

  • Utilize calibration beads with defined MESF values

  • Create standard curve of fluorescence vs. MESF values

  • Transform sample fluorescence to standardized MESF units

  • Perform quality control using reference standards

Relative Quantification Approaches:

• Fluorescence Intensity Ratios:

  • Calculate ratio of sample median fluorescence intensity (MFI) to isotype control

  • Normalize to a reference cell line included in each experiment

  • Report as fold-change relative to control populations

• Receptor Density Comparison:

  • Compare CD44 expression to other surface receptors with known copy numbers

  • Use established quantification standards like Quantum MESF beads

  • Report results as relative receptor density

Implementation Requirements:

• Maintain consistent cytometer settings between experiments

• Include calibration standards in each experimental run

• Document laser output, PMT voltages, and compensation settings

• Apply uniform analysis templates across experiments

These approaches allow researchers to move beyond arbitrary units like MFI to more biologically meaningful quantification of CD44 expression levels.

How does CD44 expression correlate with cellular differentiation and activation states?

CD44 expression dynamics provide insight into cellular differentiation and activation:

T Cell Differentiation:

• Naive T cells express low levels of CD44 (CD44low)

• Upon activation, CD44 expression increases significantly

• Memory T cells maintain high CD44 expression (CD44high)

• The combination of CD44 with CD62L distinguishes central memory (CD44highCD62Lhigh) from effector memory (CD44highCD62Llow) T cells

B Cell Activation States:

• Resting B cells express moderate CD44 levels

• Activation induces upregulation of CD44 expression

• Plasma cells typically maintain high CD44 expression

• Memory B cells show distinct CD44 expression patterns

Stem Cell Differentiation:

• CD44 expression is often high on stem/progenitor cells

• Expression patterns change during lineage commitment

• In some systems, CD44 downregulation correlates with terminal differentiation

• Dynamic regulation occurs through both transcriptional and post-translational mechanisms

Correlation with Functional States:

When analyzing CD44 in differentiation studies, it's important to:

• Track expression changes longitudinally

• Correlate CD44 levels with functional assays

• Consider CD44 isoform expression (due to alternative splicing)

• Integrate findings with broader differentiation marker panels

This dynamic regulation makes CD44 a valuable marker for tracking cellular differentiation trajectories in both normal and pathological contexts .

What factors can affect CD44 epitope detection using FITC-conjugated antibodies?

Multiple factors can influence CD44 detection and should be systematically evaluated:

Sample Preparation Factors:

• Enzymatic dissociation methods may degrade CD44 epitopes

• Fixation can alter epitope accessibility, especially for certain clones

• Freeze-thaw cycles may affect CD44 surface expression

• Storage buffer composition and pH can impact antibody binding

Antibody-Related Factors:

• FITC photobleaching due to light exposure

• Antibody degradation from improper storage

• Lot-to-lot variability in conjugation efficiency

• Clone-specific sensitivity to fixation or permeabilization

Biological Variables:

• CD44 isoform expression varies by cell type and condition

• Post-translational modifications may mask epitopes

• CD44 can be cleaved from the cell surface by proteases

• Receptor internalization following ligand binding

• Competition with endogenous hyaluronic acid

Technical Considerations:

• Suboptimal instrument settings (PMT voltage too low)

• Improper compensation leading to artificial signal reduction

• FITC spectral overlap with cellular autofluorescence

• Inadequate washing resulting in high background

Systematic Troubleshooting Approach:

• Verify antibody performance using a positive control cell line

• Test multiple antibody concentrations

• Compare different sample preparation methods

• Evaluate alternative CD44 antibody clones

• Check flow cytometer performance using standardization beads

Understanding these factors enables researchers to implement appropriate controls and optimization strategies to ensure reliable CD44 detection .

How can I reduce background and optimize signal-to-noise ratio when using CD44 Anti-Human, FITC?

Optimizing signal-to-noise ratio is critical for accurate CD44 detection:

Buffer Optimization:

• Include protein (1-2% BSA or 5-10% serum) to block non-specific binding

• Add sodium azide (0.05-0.1%) to prevent receptor internalization

• Ensure proper pH (7.2-7.4) for optimal FITC fluorescence

• Consider specialized buffers for samples with high autofluorescence

Staining Protocol Refinements:

• Increase washing steps (number and volume)

• Optimize antibody concentration through careful titration

• Reduce incubation time or temperature

• Include Fc receptor blocking reagents for samples containing Fc-bearing cells

Sample-Specific Strategies:

Advanced Approaches:

• Implement spectral unmixing to separate autofluorescence from specific signal

• Use compensation beads to accurately correct for spectral overlap

• Consider time-resolved flow cytometry to separate signal from autofluorescence

• Implement alternative conjugates with spectral properties distinct from natural autofluorescence

Data Analysis Strategies:

• Apply log or biexponential transformation for proper visualization

• Use ratio metrics rather than absolute fluorescence intensity

• Implement consistent gating strategies based on clear positive/negative discrimination

• Consider fluorescence-minus-one (FMO) controls for accurate boundary determination

Systematic optimization of these parameters enables confident detection of CD44-expressing populations even in challenging samples .

How can discrepancies in CD44 expression data between experiments be resolved?

Resolving experimental discrepancies requires methodical investigation:

Standardization Approaches:

• Process all comparison samples simultaneously when possible

• Include internal reference samples across all experimental runs

• Maintain consistent cytometer settings using calibration beads

• Document all protocol details including antibody lots, instrument settings, and analysis parameters

Common Sources of Variability:

• Technical Variables:

  • Antibody lot differences in fluorochrome:protein ratio

  • Variations in sample processing time or temperature

  • Inconsistent compensation or instrument settings

  • Changes in analysis gates or regions

• Biological Variables:

  • Cell cycle-dependent expression changes

  • Culture conditions affecting CD44 regulation

  • Sample viability differences

  • Donor-to-donor variability in primary samples

Resolution Strategies:

Documentation and Reporting:

• Record antibody lot numbers for all experiments

• Document any deviation from standard protocols

• Maintain detailed metadata about sample processing times

• Create standardized templates for data collection and analysis

• Report both absolute and normalized values when appropriate

By implementing these systematic approaches, researchers can determine whether observed differences reflect true biological variation or technical artifacts.

What is the best approach for interpreting CD44 expression in relation to other markers in multiparameter flow cytometry?

Contextual interpretation of CD44 requires integration with other markers:

Analysis Frameworks:

• Generate correlation matrices of CD44 with functionally related markers

• Implement Boolean gating to identify complex phenotypes

• Use biaxial plots to visualize relationships between CD44 and key markers

• Apply dimensionality reduction techniques (t-SNE, UMAP) for high-dimensional datasets

Biological Context Interpretation:

Integrated Analysis Approaches:

• Implement clustering algorithms (FlowSOM, Phenograph) to identify populations

• Apply trajectory analyses to map developmental progressions

• Use force-directed layouts to visualize marker relationships

• Consider machine learning for pattern recognition in complex datasets

Validation Strategies:

• Confirm key populations using different marker combinations

• Isolate populations of interest for functional validation

• Compare flow cytometry findings with alternative techniques (e.g., imaging, transcriptomics)

• Correlate CD44 patterns with biological outcomes or clinical parameters

This multifaceted approach allows researchers to extract meaningful biological insights about CD44's role in complex cellular systems .

How should CD44 expression heterogeneity be quantified and reported in research findings?

Accurately capturing CD44 heterogeneity requires sophisticated approaches:

Quantitative Metrics:

• Coefficient of variation (CV) to quantify population dispersion

• Frequency of CD44high, CD44intermediate, and CD44low subpopulations

• Shannon diversity index to measure expression diversity

• Bimodality coefficient to assess population distribution patterns

Visualization Methods:

• Overlaid histograms showing distribution shifts

• Violin plots capturing full distribution characteristics

• Contour plots to visualize population densities

• Heat maps displaying CD44 in relation to multiple parameters

Reporting Standards:

• Essential Elements:

  • Clearly defined gating strategy with illustrated examples

  • Both percentage of positive cells AND median fluorescence intensity

  • Comparison to appropriate controls (isotype, FMO)

  • Statistical measures of variation (SD, SEM, 95% CI)

• Advanced Elements:

  • Quantification of distinct expression subpopulations

  • Density distribution visualizations

  • Multiparameter correlation analysis

  • Longitudinal expression dynamics when relevant

Examples of Heterogeneity Reporting:

Comprehensive reporting of CD44 heterogeneity provides deeper insights into biological systems and facilitates meaningful comparison between studies .

How can CD44 expression data be integrated with functional assays to provide comprehensive insights?

Integrating CD44 expression with functional outcomes yields richer biological understanding:

Cell Sorting-Based Approaches:

• Sort cells based on CD44 expression levels (negative, low, intermediate, high)

• Subject sorted populations to functional assays relevant to research context

• Correlate CD44 expression intensity with functional readouts

• Perform statistical analysis to determine significance of correlations

Functional Assay Selection by Research Context:

Integration Methods:

• Correlation analysis between CD44 MFI and functional parameters

• Regression modeling to quantify predictive value of CD44

• Multivariate analysis incorporating multiple markers and functions

• Machine learning to identify complex patterns between expression and function

Validation and Extension:

• Test causality through CD44 blockade or genetic manipulation

• Perform time-course analyses to capture dynamic relationships

• Incorporate spatial information through imaging techniques

• Extend to in vivo models to confirm physiological relevance

By systematically connecting CD44 expression patterns to functional outcomes, researchers can move beyond descriptive phenotyping to mechanistic insights about CD44's role in biological processes .